Mathematical Sciences: Time Series, Extreme Values and Stochastic Models

数学科学：时间序列、极值和随机模型

• 批准号: 9006422
• 负责人: Richard Davis
• 金额: $ 1.67万
• 依托单位: Colorado State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 1990
• 资助国家: 美国
• 起止时间: 1990-07-01 至 1991-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9006422&HistoricalAwards=false
• 关键词: Mathematical; Sciences; Time; Series; Extreme

The principal investigators will work in the area of time series analysis and stochastic modeling. The work is divided into two parts. The first part is concerned with problems of estimation and prediction for time series models whose theory is not yet fully understood. These include non-linear, heavy tailed and non-Gaussian processes, all of which play a role in the modelling of real time series data. Efficient estimation and prediction procedures for such series will be sought and their properties will be investigated. Some relatively unexplored models will be considered and some new techniques for state-space modelling of multivariate time series will be investigated. The second part deals with extreme value theory, particularly the interplay between extreme value methods, point processes, asymptotic theory and the application of these ideas to linear, bilinear and general stationary processes.

主要调查人员将在时间范围内工作 序列分析和随机建模。 工作分工 分成两部分。 第一部分是关于 估计和预测的时间序列模型，其理论是 尚未完全理解。 其中包括非线性、重 尾部和非高斯过程，所有这些都在 真实的时间序列数据的建模。 有效估计 将寻求这种系列的预测程序， 他们的财产将被调查。 一些相对 将考虑未探索的模型和一些新的技术， 多变量时间序列的状态空间建模将是 研究了 第二部分是极值理论， 特别是极值方法之间的相互作用， 过程，渐近理论和这些思想的应用 线性、双线性和一般平稳过程。